# How to stack rasters for ecological analysis?

The attached image shows two different forest openings. Each opening has the following layers associated with it:

1. Point shapefile 1 = A red X which represent a large "legacy" tree in the gap
2. Point shapefile 2 = White points that indicate sapling locations
3. Raster Layer = A kernel density estimate of the magnitude per unit area of point shapefile 2

I am interested in creating a graphic that visually depicts the average magnitude per unit area between the two rasters. Each raster has a different spatial extent. My thoughts were to "stack" the rasters based on the location of point shapefile 1 (i.e. the legacy tree) and perform the analysis using raster algebra (e.g. Float("Raster1" + "Raster2")/2). I should point out that the full dataset will have ~ 30 forest openings.

How can I stack these rasters so that they are centered on the legacy tree in order to perform the raster algebra?

Edit:

As @Alexandre pointed out, the solution was to georeference the rasters based on X.

• Can't you just calculate the coordinate difference between the crosses (x2-x1, y2-y1) and perform a simple translation to the "second" raster? Jan 4, 2013 at 21:47
• @Alexandre Neto Good idea--although, I'm not really sure how to implement it.
– Aaron
Jan 4, 2013 at 22:07
• Do you really need it to be done using a python script? Or you only need it done once? The raster are in what format? Jan 4, 2013 at 22:25
• @Alexandre I only need to perform the actions once. The raster format can be anything--the example I showed used .img.
– Aaron
Jan 4, 2013 at 22:28
• I don't really know if this works, But you can try usingthe georeferencing tool to translate the second raster. You would use the trees location as refecence to create a single ground control point (GCP). Generally, you use 3 control point, but since we don't want to change the scale or the angle of the raster, if arcgis allows you to transform the raster with only one control point, it will probably get the job done. Jan 4, 2013 at 22:43